首页 | 本学科首页   官方微博 | 高级检索  
     

一种2_a_2支持向量机多类分类新方法
引用本文:于清,赵晖. 一种2_a_2支持向量机多类分类新方法[J]. 计算机工程与应用, 2008, 44(25): 186-188. DOI: 10.3778/j.issn.1002-8331.2008.25.056
作者姓名:于清  赵晖
作者单位:新疆大学信息科学与工程学院,乌鲁木齐,830046;新疆大学信息科学与工程学院,乌鲁木齐,830046
基金项目:教育部科学技术基金,新疆高校科研计划 
摘    要:提出一种2_a_2支持向量机多类分类新方法,它的优点是充分利用了每个子分类器的识别结果,将最少数量的子分类器组合在一起,实现多类分类。通过对CMU表情库4种不同表情图像的分类识别实验表明,该算法能明显提高识别速率。将该方法应用于解决更多类的分类问题时,同样体现出优越性。

关 键 词:支持向量机(SVM)  多类分类  2_a_2方法
收稿时间:2008-05-14
修稿时间:2008-7-28 

New method of 2_a_2 to Support Vector Machine multi-class classification
YU Qing,ZHAO Hui. New method of 2_a_2 to Support Vector Machine multi-class classification[J]. Computer Engineering and Applications, 2008, 44(25): 186-188. DOI: 10.3778/j.issn.1002-8331.2008.25.056
Authors:YU Qing  ZHAO Hui
Affiliation:College of Information and Engineering,Xinjiang University,Urumqi 830046,China
Abstract:A new method of 2_a_2 SVM multi-class classification is put forward,the advantage of which is to make good use of the results of each sub-classifier so that the problem of classification of different classes can be resolved only by using the smallest numbers of sub-classifiers.In order to verify the effectiveness of this method,experiments have been made on CMU database,and the experimental results are satisfactory.If this method is applied to resolve the problem of classification of lots of classes,comparing with the current methods,it also has the same advantage.
Keywords:Support Vector Machine(SVM)  multi-class classification  2_a_2 method
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号